536 citations · 1.3k across the 27 of their papers we have counts for
6 papers · 1 filter
Unsupervised Spatial-spectral Network Learning for Hyperspectral Compressive Snapshot Reconstruction
Yubao Sun, Ying Yang, Qingshan Liu +1
Hyperspectral compressive imaging takes advantage of compressive sensing theory to achieve coded aperture snapshot measurement without temporal scanning, and the entire three-dimen…
Meta-Learning with Network Pruning
Hongduan Tian, Bo Liu, Xiao-Tong Yuan +1
Meta-learning is a powerful paradigm for few-shot learning. Although with remarkable success witnessed in many applications, the existing optimization based meta-learning models wi…
Adaptive Graph Convolutional Network with Attention Graph Clustering for Co-saliency Detection
Kaihua Zhang, Tengpeng Li, Shiwen Shen +3
Co-saliency detection aims to discover the common and salient foregrounds from a group of relevant images. For this task, we present a novel adaptive graph convolutional network wi…
Dual Temporal Memory Network for Efficient Video Object Segmentation
Kaihua Zhang, Long Wang, Dong Liu +3
Video Object Segmentation (VOS) is typically formulated in a semi-supervised setting. Given the ground-truth segmentation mask on the first frame, the task of VOS is to track and s…
Classification of Hyperspectral and LiDAR Data Using Coupled CNNs
Renlong Hang, Zhu Li, Pedram Ghamisi +3
In this paper, we propose an efficient and effective framework to fuse hyperspectral and Light Detection And Ranging (LiDAR) data using two coupled convolutional neural networks (C…
Video Saliency Prediction Using Enhanced Spatiotemporal Alignment Network
Jin Chen, Huihui Song, Kaihua Zhang +2
Due to a variety of motions across different frames, it is highly challenging to learn an effective spatiotemporal representation for accurate video saliency prediction (VSP). To a…